No / The comet assay or single-cell gel electrophoresis assay is a relatively simple and sensitive technique for quantitatively measuring DNA damage and repair at the single-cell level in all types of tissue where a single-cell suspension can be obtained. Isolated cells are mixed with agarose, positioned on a glass slide, and then lysed in a high-salt solution which removes all cell contents except the nuclear matrix and DNA, which is finally subjected to electrophoresis. Damaged DNA is electrophoresed from the nuclear matrix into the agarose gel, resembling the appearance of a comet, while undamaged DNA remains largely within the proximity of the nuclear matrix. By choosing different pH conditions for electrophoresis, different damage types and levels of sensitivity are produced: a neutral (pH 8–9) electrophoresis mainly detects DNA double-strand breaks, while alkaline (pH ≥ 13) conditions detect double- and single-strand breaks as well as alkali-labile sites. This protocol describes a standard comet assay study for the analysis of DNA damage and outlines important variations of this protocol.

This research investigates the application of machine learning techniques in computational genomics across two distinct domains: (1) the predicting the source of bacterial pathogen using whole genome sequencing data, and (2) the functional annotation of genes using single- cell RNA sequencing data. This work proposes the development of a bioinformatics pipeline tailored for identifying genomic variants, including gene presence/absence and single nu- cleotide polymorphism. This methodology is applied to specific strains such as Salmonella enterica serovar Typhimurium and the Ralstonia solanacearum species complex. Phylo- genetic analyses along with pan-genome and positive selection studiesshow that genomic variants and evolutionary patterns of S. Typhimurium vary across sources, which suggests that sources can be accurately attributed based on genomic variants empowered by machine learning. We benchmarked seven traditional machine learning algorithms, achieving a no- table accuracy of 94.6% in host prediction for S. Typhimurium using the Random Forest model, underscored by SHAP value analyses which elucidated key predictive features. Next, the focus is shifted to the prediction of Gene Ontology terms for Arabidopsis genes using single-cell RNA-seq data. This analysis offers a detailed comparison of gene expression in root versus shoot tissues, juxtaposed with insights from bulk RNA-seq data. The integration of regulatory network data from DAP-seq significantly enhances the prediction accuracy of gene functions. / Master of Science / This work applies machine learning techniques to two areas in computational biology: pre- dicting the hosts of bacterial pathogens based on their genome data, and predicting the func- tions of plant genes using single-cell gene expression data. The first part develops a method to analyze genome sequences from bacterial pathogens like Salmonella enterica serovar Ty- phimurium and the Ralstonia solanacearum species complex, identifying genomic variants, including gene presence/absence and single nucleotide polymorphism, which are variations in genetic code. By studying the evolutionary relationships and genetic diversity among dif- ferent strains, the motivation for using machine learning models to predict the sources (e.g., poultry, swine) of the pathogen genomes is established. Several machine learning models are then trained on these datasets, and the most important factors contributing to the predic- tions are identified. The second part focuses on predicting the functions of genes in the model plant species Arabidopsis thaliana using the gene expression data measured at the single-cell level to train machine learning models for identifying standardized gene function descrip- tions called Gene Ontology (GO) terms. By comparing results from single-cell and bulk tissue data, the study evaluates whether the higher resolution of single-cell data improves gene function prediction accuracy. Additionally, by incorporating information about gene regulation from a specialized experiment, the role of gene expression control in determining gene functions is explored.

Cells have been found to have an inherent heterogeneity that has led to an increase in the development of single-cell analysis methods to characterize the extent of heterogeneity that can be found in seemingly identical cells. With an understanding of normal cellular variability, the identification of disease induced cellular changes, known as biomarkers, may become more apparent and readily detectable. Biomarker discovery in single-cells is challenging and needs to focus on molecules that are abundant in cells. Lipids are widely abundant in cells and play active roles in cellular signaling, energy metabolism, and are the main component of cellular membranes. The regulation of lipid metabolism is often disrupted or lost during disease progression, especially in cancer, making them ideal candidates as biomarkers. Challenges exist in the analysis of lipids beyond those of single-cell analysis. Lipid extraction solvents must be compatible with the lipid or lipids of interest. Many lipids are isobaric making mass spectrometry analysis difficult without separations. Single-cell extractions using nanomanipulation coupled to mass spectrometry has shown to be an excellent method for lipid analysis of tissues and cell cultures. Extraction solvents are tunable for specific lipid classes, nanomanipulation prevents damage to neighboring cells, and lipid separations are possible through phase dispersion. The most important aspect of single-cell analysis is that it uncovers the extent of cellular heterogeneity that exists among cellular populations that remains undetected during averaged sampling.

Im ersten Teil der Arbeit wurden Strategien zur Analyse von Transkripten erarbeitet. Die ersten Versuche zielten darauf ab, in mit Glaskapillaren genommenen Einzelzellproben verschiedener Gewebeschichten RT-PCR durchzuführen, um spezifische Transkripte nachweisen zu können. Dies gelang für eine Reihe von Genen aus verschiedenen Pflanzenspezies. Dabei konnten sowohl Transkripte stark wie auch schwach exprimierter Gene nachgewiesen werden. <br /> Für die Erstellung von Gewebe-spezifischen Expressionsprofilen war es notwendig, die in vereinigten Zellproben enthaltene mRNA zunächst zu amplifizieren, um eine ausreichende Menge für Arrayhybridisierungen zu erhalten. Vor der Vermehrung wurde die mRNA revers transkribiert. Es wurden daran anschließend verschiedene Amplifikationsstrategien getestet: Die neben Tailing, Adapterligation und anderen PCR-basierenden Protokollen getestete Arbitrary-PCR hat sich in dieser Arbeit als einfache und einzige Methode herausgestellt, die mit so geringen cDNA-Mengen reproduzierbar arbeitet. Durch Gewebe-spezifische Array-hybridisierungen mit der so amplifizierten RNA konnten schon bekannte Expressionsmuster verschiedener Gene, vornehmlich solcher, die an der Photosynthese beteiligt sind, beobachtet werden. Es wurden aber auch eine ganze Reihe neuer offensichtlich Gewebe-spezifisch exprimierter Gene gefunden. Exemplarisch für die differentiell exprimierten Gene konnte das durch Arrayhybridisierungen gefundene Expressionsmuster der kleinen Untereinheit von Rubisco verifiziert werden. Hierzu wurden Methoden zum Gewebe-spezifischen Northernblot sowie semiquantitativer und Echtzeit-Einzelzell-RT-PCR entwickelt.<br /> Im zweiten Teil der Arbeit wurden Methoden zur Analyse von Metaboliten einschließlich anorganischer Ionen verwendet. Es stellte sich heraus, daß die multiparallele Methode der Gaschromatographie-Massenspektrometrie keine geeignete Methode für die Analyse selbst vieler vereinigter Zellinhalte ist. Daher wurde auf Kapillarelektrophorese zurückgegriffen. Eine Methode, die mit sehr kleinen Probenvolumina auskommt, eine hohe Trennung erzielt und zudem extrem geringe Detektionslimits besitzt. Die Analyse von Kohlenhydraten und Anionen erfordert eine weitere Optimierung. Über UV-Detektion konnte die K+-Konzentration in verschiedenen Geweben von A. thaliana bestimmt werden. Sie lag in Epidermis und Mesophyll mit ca. 25 mM unterhalb der für andere Pflanzenspezies (Solanum tuberosum und Hordeum vulgare) publizierten Konzentration. Weiter konnte gezeigt werden, daß zwölf freie Aminosäuren mittels einer auf Kapillarelektrophorese basierenden Methode in vereinigten Zellproben von Cucurbita maxima identifiziert werden konnten. Die Übertragung der Methode auf A. thaliana-Proben muß jedoch weiter optimiert werden, da die Sensitivität selbst bei Laser induzierter Fluoreszenz-Detektion nicht ausreichte.<br /> Im dritten und letzten Teil der Arbeit wurde eine Methode entwickelt, die die Analyse bekannter wie unbekannter Proteine in Gewebe-spezifischen Proben ermöglicht. Hierzu wurde zur Probennahme mittels mechanischer Mikrodissektion eine alternative Methode zur Laser Capture Microdissection verwendet, um aus eingebetteten Gewebeschnitten distinkte Bereiche herauszuschneiden und somit homogenes Gewebe anzureichern. Aus diesem konnten die Proteine extrahiert und über Polyacrylamidgelelektrophorese separariert werden. Banden konnten ausgeschnitten, tryptisch verdaut und massenspektrometrisch die Primärsequenz der Peptidfragmente bestimmt werden. So konnten als Hauptproteine im Mesophyll die große Untereinheit von Rubisco sowie ein Chlorophyll bindendes Protein gefunden werden.<br /> Die in dieser Arbeit entwickelten und auf die Modellpflanze Arabidopsis thaliana angewandten Einzelzellanalysetechniken erlauben es in Zukunft, physiologische Prozesse besser sowohl räumlich als auch zeitlich aufzulösen. Dies wird zu einem detaillierteren Verständnis mannigfaltiger Vorgänge wie Zell-Zell-Kommunikation, Signalweiterleitung oder Pflanzen-Pathogen-Interaktionen führen. / The subject of this thesis was the analysis of single plant cells in respect to their contents of i) transcripts, ii) inorganic cations and anions, iii) metabolites like amino acids and carbohydrates as well as iv) proteins. One task was the transfer of existing methods to single cell analysis on leaf tissues of the model plant Arabisopsis thaliana L., the second one was the refinement and the development, respectively, of new protocols for the analysis of such picoliter samples. For cell type specific sampling two different complimentary methods were applied: Using micro glass capillaries specific single cell contents could be harvested from intact plants, whereas typical sample volumes were in the picoliter range. Even the sampling of inner cell types such as companion cells could be demonstrated. Using mechanical micro dissection of embedded tissue a larger amount of homogenous tissue could be collected.<br /> Because single cell samples contain only femtogram amounts of mRNA, direct detection of transcripts is impossible. Therefore, two amplification protocols were applied to the cell samples: The first procedure makes use of specifically primed RT-PCR for amplification. Several genes derived from different plants and tissues could be detected after successful RT-PCR, including high as well as low expressed genes. The second method was developed to monitor the activity of many genes in parallel using array hybridisation with filters containing the cDNA of as many as 16.000 ESTs. For this purpose, unspecific RT-PCR as it is applied in the differential display was used to amplify different transcripts in just one reaction. However, in these tissue specific array hybridisations the expression patterns of several hundreds genes could be monitored. These included known tissue specific expression patterns (of mainly photosynthesis related genes) as well as a couple of unknown expression patterns. To verify the tissue specificity of gene activity some results were reconsidered using tissue specific northern blot hybridisations and real time RT-PCR, respectively. <br /> Secondly, metabolites (including inorganic ions) were investigated: Because gas chromatography-mass spectrometry does not reveal the sensitivity which in necessary for the analysis of even multiple pooled single cell samples capillary electrophoresis was applied for these studies. This method has a high potential as it needs only small amounts of starting material, has uncomparable low detection limits and exhibits a high number of theoretical plates.<br /> The analysis of inorganic anions and carbohydrates needs further optimisations. Using UV absorption-detection potassium could be detected in different cell types whereas the concentrations in mesophyll and epidermis were found around 25 mM each. These concentrations are lower than in other species as Solanum tuberosum or Hordeum vulgare. For investigations of amino acids the cell samples were derivatized to make the use of laser induced fluorescence-detection capable. In samples derived from pumpkin (Cucurbita maxima) mesophyll twelve amino acids could be detected and identified. The transfer of this method to A. thaliana derived samples exhibited no results which may be due to the low concentration of free amino acids in these plants.<br /> Finally, a method was developed with which the existence of known and unknown proteins in tissue specific samples could be monitored. For this, mechanical micro dissection was used to: After embedding and sectioning the tissue of interest was cut out by an vibrating steel chisel to get homogenous samples. The proteins contained in these tissue pieces were extracted and separated by one dimensional SDS polyacrylamid gel electrophoresis. Several protein bands could be detected after staining with either silver or coomassie blue stain. These bands were cut out and sequenced by mass spectrometry. The large subunit of rubisco as well as one chlorophyll binding protein could be identified as the major proteins within the mesophyll.<br /> The single cell analysis methods which were developed and applied to the model plant A. thaliana in this thesis allow a better spatial as well as temporal resolution of analysis. This will lead to a more detailed understanding of physiological processes like cell to cell communication, signalling or plant-pathogen interactions.

Today many cell biological techniques study large cell populations where an average estimate of individual cells’ behavior is observed. On the other hand, single cell analysis is required for studying functional heterogeneities between cells within populations. This thesis presents work that combines the use of microfluidic devices, optical microscopy and automated image analysis to design various cell biological assays with single cell resolution including cell proliferation, clonal expansion, cell migration, cell-cell interaction and cell viability tracking. In fact, automated high throughput single cell techniques enable new studies in cell biology which are not possible with conventional techniques. In order to automatically track dynamic behavior of single cells, we developed a microwell based device as well as a droplet microfluidic platform. These high throughput microfluidic assays allow automated time-lapse imaging of encapsulated single cells in micro droplets or confined cells inside microwells. Algorithms for automatic quantification of cells in individual microwells and micro droplets are developed and used for the analysis of cell viability and clonal expansion. The automatic counting protocols include several image analysis steps, e.g. segmentation, feature extraction and classification. The automatic quantification results were evaluated by comparing with manual counting and revealed a high success rate. In combination these automatic cell counting protocols and our microfluidic platforms can provide statistical information to better understand behavior of cells at the individual level under various conditions or treatments in vitro exemplified by the analysis of function and regulation of immune cells. Thus, together these tools can be used for developing new cellular imaging assays with resolution at the single cell level. To automatically characterize transient migration behavior of natural killer (NK) cells compartmentalized in microwells, we developed a method for single cell tracking. Time-lapse imaging showed that the NK cells often exhibited periods of high motility, interrupted with periods of slow migration or complete arrest. These transient migration arrest periods (TMAPs) often overlapped with periods of conjugations between NK cells and target cells. Such conjugation periods sometimes led to cell-mediated killing of target cells. Analysis of cytotoxic response of NK cells revealed that a small sub-class of NK cells called serial killers was able to kill several target cells. In order to determine a starting time point for cell-cell interaction, a novel technique based on ultrasound was developed to aggregate NK and target cells into the center of the microwells. Therefore, these assays can be used to automatically and rapidly assess functional and migration behavior of cells to detect differences between health and disease or the influence of drugs. The work presented in this thesis gives good examples of how microfluidic devices combined with automated imaging and image analysis can be helpful to address cell biological questions where single cell resolution is necessary. / <p>QC 20130927</p>

An EU-funded project Fit-4-AMandA aims to establish a technological roadmap to scale-up from less than hundred stacks/year (manual assembly) to 50,000 stacks/year (automated assembly) in 2020 and beyond. Existing membrane-electrode assembly (MEA) and stack were redesigned/adapted for manufacturability and automation. The technology and machine system for the automated assembly of polymer-electrolyte-membrane fuel cell (PEMFC) stacks were developed, manufactured and are currently being tested. Fast in-line non-destructive quality-assurance methods for automated production of MEAs and stack assembly are being developed and implemented. For the final period of the project, a validation of the designs, hardware, tools and software for the automated production of MEAs and stack assembly as well as an integration of one of the prototype stacks manufactured by the automated processes into a light-commercial vehicle followed by a field-testing are scheduled. / Die breite Markteinführung von wasserstoffbasierten Antriebssystemen verlangt zunehmend nach einer kosteneffizienten und serientauglichen Produktion von Brennstoffzellenstacks. So sehen die Ziele der Europäischen Union vor, die Herstellung von aktuell unter 100 Stacks pro Jahr auf 50.000 Stacks pro Jahr bis zum Jahr 2020 zu erhöhen. Um dies zu erreichen, sollen im Rahmen des vom Fuel Cell and Hydrogen Joint Undertaking (FCH JU) der europäischen Union geförderten Projektes Fit-4-AMandA automatisierte Anlagen für solche Stückzahlen befähigt werden. Der Beitrag beschreibt, wie die bereits verfügbare Membran-Elektroden-Einheit (MEA) und der Stack bezüglich Herstellbarkeit und Automatisierung konstruktiv umgestaltet und angepasst wurden. Die neu entwickelte Technologie und das Maschinensystem für die automatisierte Montage von PEM-FC-Stacks sowie Verfahren der INLINE-Qualitätssicherung und der zerstörungsfreien Prüfung werden mit ihren Implementierungsmöglichkeiten in die automatisierte Fertigungsstrecke vorgestellt. Ein Ausblick gibt eine Übersicht über die weiteren Entwicklungsschritte wie die Validierung der Entwürfe, der Hard- und Software für die automatisierte Produktion der MEAs und Stacks. Eine vorgesehene spätere Integration der so gefertigten Stacks in ein Fahrzeug und die damit verbundenen Feldtests zur Untersuchung der Reproduzierbarkeit und Zuverlässigkeit der Stacks werden abschließend dargestellt. Die Förderung des Projektes erfolgt im Rahmen der Finanzhilfevereinbarung Nr. 735606 des FCH JU der EU.

The increased frequencies of two novel B cell populations defined as IgM+ CD19+ CD27- CD21low CD38low CD24+ and IgM+ CD19+ CD27- CD21low CD38low CD24- in peripheral blood of patients with common variable immunodeficiency (CVID) compared to healthy donors were found. The aim was to search for such B cells in patients with rheumatoid arthritis (RA) and their further characterization. The production of immunoglobulin (Ig) mRNA in single B cells was analyzed using flow cytometry, single cell sorting and RT-PCR, IgVH-specific PCR, cycle sequencing and statistical analysis. The study was focused on analysis of variable regions of the heavy chains of Igs and significant differences in the usage of VH, DH and JH gene segments, mutational frequencies, distribution of silent and replacement mutations, length and composition of CDR3 regions, clonal relation and RAG gene expression in above mentioned B cell populations were found. Because of lack of the surface CD27 molecule being regarded as marker of B cells that have undergone antigen-driven germinal reactions, analyzed populations were considered as naive. However, the pattern and type of mutations suggested that these cells could represent a new type of differentiated memory/antigen- experienced B lymphocytes (in CVID less maturated) with the likely role in...

Disertační práce je zaměřena na nízkoenergetické konvertory pro zpracování energie. Pro fotovoltaické generátory pracující při nízké úrovní osvětlení byly navrženy konvertory založené na konfiguraci single cell. Pomocí levných výrobních procesů a dostupných materiálů byl navržen a vyroben jednoduchý a spolehlivý termogenerátor. Výrobní postupy využívaly plazmatické aktivace povrchu pomocí výboje s dielektrickou bariérou a modifikované metody depozice PEDOT. Byly navrženy jednoduché a spolehlivé DC/DC měniče pro nízkonapěťové aplikace jako termoelektrické generátory a fotovoltaické články v konfiguraci single cell. Měniče pracují od napětí několika desítek mV a výstupní napětí může být na úrovni několika voltů. Účinnost se blíží 50% a náklady na materiál a výrobu jsou ve srovnání s použitím běžně dostupných integrovaných obvodů pro Energy Harvesting výrazně nižší. Pro řídicí obvody byly použity bipolární tranzistory, které v režimu velmi malých proudů mohou mít napájecí napětí od 0,5 V. Byla ověřena možnost výroby integrovaných obvodů s extrémně nízkým provozním napětím. Tranzistory FET zde pracují v podprahovém režimu a v režimu Bulk-driven.

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Doctor of Philosophy / Department of Grain Science and Industry / Praveen V. Vadlani / As the world population continues to grow and the uncertainty of petroleum and food availability transpires, alternative resources will be needed to meet our demands. Single cell oil (SCO) from oleaginous yeast is a renewable noncrop-based resource that can be used for the production of petroleum counterparts. Currently, commercial production is limited, mainly due to high production costs and competition from cheaper alternatives. As a result, improved fermentation techniques, utilization of low-valued feedstocks and efficient downstream processing would be highly valuable. The major objectives of this study were to: 1) optimize fermentation conditions for the development of a novel fed-batch fermentation to enhance oil production using Lipomyces starkeyi, 2) determine the major lipids produced by L. starkeyi, 3) utilize low-valued hemicellulose-rich feedstocks for oil production, and 4) demonstrate the use of 2-methyltetrahydrofuran (2-MeTHF) and cyclopentyl methyl ether (CPME) as greener solvents for oil extraction. Under optimized fermentation conditions, the oil yield increased from 78 to 157 mg oil/g sugar when supplying xylose rather than glucose as the major carbon source. A novel repeated fed-batch fermentation supplying glucose for growth and xylose for lipid accumulation generated the highest oil yield of 171 mg oil/g sugar, oil content of 60% (dry mass basis) and oil productivity of 143 mg oil/L/hr. Oleic acid accounted for 70% of the total fatty acid profile indicating that oil from L. starkeyi is a naturally high source of oleic acid; an added benefit for the biofuel, cosmetic, food, and oleochemical industries. Hemicellulose-rich corn bran and wheat bran were successfully used to produce oil; oil yields of 125 and 71 mg oil/g sugar were reported for whole and de-starched bran hydrolysates, respectively. Compared to traditional methods, biphasic oil extraction systems of 2-MeTHF and CPME had an 80 and 53% extraction efficiency and 64 and 49% selectivity, respectively. The information from this study will be useful for the development of an integrated approach to improve the viability of SCO biochemical platforms for the production of advanced biofuels and renewable chemicals.